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102 Cards in this Set
- Front
- Back
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Experimental Research
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Quantitative- researcher, intervention, or treatment
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Phenomenology
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Qualitative- Peoples experience in regards to phenomena
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Phenomenology
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Qualitative- Peoples experience in regards to phenomena
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Grounded theory Research
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Qualitative- Social structure, and social interactions
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Ethnography Research
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Qualitative- the study of a group of living people
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Experimental Research
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Quantitative- researcher, intervention, or treatment
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Quazi-Experimental
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Quantitative- control trial without randomization
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descriptive research
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non-experimental/ quantitative- describes data and characteristics about the population or phenomenon being studied
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Correlational Research
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Non-experimental/ quantitative - Gives an indication of how 2 variables interact. CAN NOT say one causes the other.
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Continuous Variable
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take on any value (can be a decimal)
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Discrete Variable
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a whole number
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Categorical Variable
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variable that uses words
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conceptual definition
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abstract or theoretical meaning of the concepts being studied (pain)
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operational definition
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procedures required to measure a variable (pain scale)
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Problem Statements
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well-structured formulation of what it is that is problematic; argument of the need for a study
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Problem Statement components
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problem identification, background, scope of the problem, concequences of the problem, knowledge gaps, proposed solution
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Purpose Statement quantitative
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Quantitative- summary of the overall goal of a study; predicts relationship between 2 or more variables through hypotheses
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Purpose Statement qualitative
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nature of inquiry; key concept or phenomena;
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Significant Study
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impact nursing practice, builds on previous research, promotes theory testing or development
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Research Hypotheses
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Quantitative- prediction about relationship between 2 or more variables
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simple hypotheses
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quantitative- relationship between 2 variables
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complex hypotheses
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quantitative- relationship among 3 or more variables
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directional hypotheses
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quantitative- tells the expected direction of a relationship
increase/decrease |
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nondirectional hypothesis
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quantitative- no indication of direction (blah affects blah)
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Research Hypothesis
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Predict the existence of relationships
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methodology
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design, sample, setting, procedure, measures, data analysis
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Results
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data analysis results, tables for the analysis results, NO REFERENCES
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Discussion
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interpretation of the findings, limitations, implications, recommendations, conclusions
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Discussion
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interpretation of the findings, limitations, implications, recommendations, conclusions
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Literature Review
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A summary of current knowledge on topic/ what is not known on topic
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Quantitative Lit review
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Comprehensive lit review essential at beginning of project and updated @ end of project
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Qualitative lit review
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comprehensive lit review sometimes delayed till after collection
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Systematic review
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A rigorous and systematic synthesis of researcher findings on common or strongly related research question
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Concept
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Basic building blocks of a theory
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theories
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set of ideas that explain how things are related
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Conceptual models of nursing
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Human beings, environment, health, nursing
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Conceptual models of nursing
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Human beings, environment, health, nursing
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King
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Goal attainment
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leininger
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culture care theory
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qualitative research theories
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theory is the result not the starting point... but they can start from broad theories
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quantitative research theories
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test a theory, compare two theories, test an intervention derived from a theory
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Positivist paradigm
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quantitative- reality exist and is driven by real natural causes and not influenced by researcher
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design
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ummm road map to conduct a study, that maximizes control over factors that could interfere with the validity of the findings
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quantitative research design
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describe, compare, discover, and cause and effect
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qualitative research design
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discover of meaning, not cause and effect, no IV or DV
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true experimental design
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control group, randomization, manipulation, to provide the greatest amount of control possible to examine causality
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pretest-posttest design
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greater the control over the experimental environment the less the ability to generalize beyond the specific sample study
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pretest-posttest design
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greater the control over the experimental environment the less the ability to generalize beyond the specific sample study
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true experimental limitations
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artificial, narrow, maintaining integrity and consistency, participation, placebo effect
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quasi-experimental designs
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use when true experimental control is not practical or ethical, goal= control as many threats to validity as possible
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descriptive design
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is considered with prevalence and incidence
risky behavior -> STDs |
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controlling intrinsic factors
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randomization, homogeneity, matching subjects, and statistical control
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controlling intrinsic factors
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randomization, homogeneity, matching subjects, statistical control
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internal validity
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make an inference that the IV is causing or influencing the DV
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Threats to internal validity
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temporal ambiguity, selection, history, maturation, mortality/ attrition
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Threats to internal validity
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temporal ambiguity, selection, history, maturation, mortality/ attrition
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external validity
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relationships observed in a study hold true for different people, conditions, and settings
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threats to external validity
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sampling error and environment
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construct validity
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is the intervention a good representation to have beneficial influence on DV
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snowballing sampling
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quantitative non probability
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consecutive sampling
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quantitative non probability- get people form population who meet eligibility criteria over a specific time interval
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quota sampling
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quantitative non probability- identifies variables to stratify by, and then finds participants by convenience
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Purposive sampling
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qualitative non probability- sample group is hand picked
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simple random sampling
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quantitative probability sampling- random selection from a sampling frame
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stratified random sampling
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commonly used variables for stratification
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cluster sampling
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quantitative probability sampling- divided into groups and then a sample of the group is selected
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systemic sampling
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eg. every 10th person in the roster
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sample size
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power analysis, to see how big a sample needs to be
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Data collection methods
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structured self report, observation, biophysical measure
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response bias
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social desirability, response sets eg bond eval
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in vivo
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measuring directly on the living organism
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in vitro
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taking something from the living organism and measuring it in lab
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Q-sort
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clients sort cards according to their importance
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reliability
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consistency, stability, dependability
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validity of instrument
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accuracy
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design validity
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does the research allow the investigator to answer their hypothesis
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cronbach alpha reliability estimates
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>0.90 excellent
.80 good .7 adequate |
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Face Validity
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looks like a duck walks like a duck
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Content validity
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all the major elements relevant to the construct being measured
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Criterion Validity
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the degree to which scores on an instrument are correlated with some external criterion (pain with facial)
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sensitivity
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quantitative- true positivessssss
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specificity
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quantitative- true negatives-----
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parameter
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a numerical quantity that describes some characteristic of a population (mean, SD)
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statistic
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quantitative value that is calculated from the observations in a sample
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Type 1 error
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false POSITIVE rejecting true Ho
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Type 2 error
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false negative- fail to reject false Ho
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T- test
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test mean difference between 2 groups
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analysis of variance
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test mean differences in greater than 3 groups
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parametric
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estimation of parameter, interval/ratio scale, normal distribution, more powerful than nonparametric
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nonparametric
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distribution free scale- nominal/ordinal
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Chi-square test
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nonparametric procedure- test difference in proportions in 2+ independent groups
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founder of symbolic interactionism
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george herbert mead
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founder of Phenomenology
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edmonds husserl
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Rigor- qualitative Truth in Value
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Credibility- confidence in the truth of the data and interpretations of them
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Rigor- qualitative Applicability
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Transferability-
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Rigor- Qualitative Consistency
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Dependability- stability of data over time
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Rigor- Qualitative Neutrality
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confimability- congruence between 2 or more I people about the datas accuracy and meaning
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Rigor- quantitative Truth in value
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Internal validity
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Rigor- Quantitative Applicability
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external validity
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Rigor- Quantitative Consistency
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reliability
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Rigor- Quantitative neutrality
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objectivity
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Issues in Data Collection
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gaining trust, pace of data collection, emotional involvement with participants, reflexivity
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